Instructions to use tiiuae/falcon-7b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tiiuae/falcon-7b-instruct with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="tiiuae/falcon-7b-instruct", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("tiiuae/falcon-7b-instruct", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("tiiuae/falcon-7b-instruct", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use tiiuae/falcon-7b-instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tiiuae/falcon-7b-instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tiiuae/falcon-7b-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/tiiuae/falcon-7b-instruct

SGLang

How to use tiiuae/falcon-7b-instruct with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "tiiuae/falcon-7b-instruct" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tiiuae/falcon-7b-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "tiiuae/falcon-7b-instruct" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tiiuae/falcon-7b-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use tiiuae/falcon-7b-instruct with Docker Model Runner:
```
docker model run hf.co/tiiuae/falcon-7b-instruct
```

ValueError: not enough values to unpack (expected 4, got 3)

by veilsidebr - opened May 28, 2023

Discussion

veilsidebr

May 28, 2023

Hi there! Using the 7b instruct model, i used the code provided in model card, saved as main.py and when i run it, i keep receiving this error after 3-5 mins processing, any ideas of what may be wrong?

C:\Users\veilsidebr/.cache\huggingface\modules\transformers_modules\tiiuae\falcon-7b-instruct\b6 │
│ efaea5d78e4313145bda4d688675414a76fc22\modelling_RW.py:478 in _convert_to_rw_cache │
│ │
│ 475 │ def _convert_to_rw_cache( │
│ 476 │ │ past_key_value: Tuple[Tuple[torch.Tensor, torch.Tensor]] │
│ 477 │ ) -> Tuple[Tuple[torch.Tensor, torch.Tensor]]: │
│ ❱ 478 │ │ batch_size, num_heads, head_dim, seq_length = past_key_value[0][0].shape │
│ 479 │ │ batch_size_times_num_heads = batch_size * num_heads │
│ 480 │ │ # key: [batch_size, num_heads, head_dim, seq_length] -> [batch_size * num_heads │
│ 481 │ │ # value: [batch_size, num_heads, seq_length, head_dim] -> [batch_size * num_head │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ValueError: not enough values to unpack (expected 4, got 3)
PS C:\Models\Falcon-7B>

taurasAI

Jun 28, 2023

Try upgrading package from transformers to latest version
I upgraded transformers to 4.30.2 and this issues is resolved
P.S torch=2.0.1

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